无线电工程2025，Vol.55Issue(3)：672-678,7.DOI:10.3969/j.issn.1003-3106.2025.03.025
基于潜博弈的多传感器协同跟踪分布式优化算法
Distributed Optimal Algorithm Based on Potential Game for Multi-sensor Collaborative Tracking
摘要
Abstract
A distributed optimal assignment algorithm based on potential game theory is proposed to solve the partially observable multi-sensor collaborative tracking problem.The sensor is selected as the game player and the multi-sensor multi-target assignment problem under detection and communication constrains is constructed as a game model based on local information with the target tracking reward function of Generalized Fisher Information Matrix(GFIM)metric.The model is proved to be a potential game model with at least one feasible pure strategy Nash Equilibrium(NE)point.A Modified Parallel Best Response Dynamic(MPBRD)algorithm is developed to solve the game problem efficiently.Then its computation complexity is analyzed.Simulation results show that in small-scale scenario,the proposed algorithm can achieve the tracking performance of the full enumeration algorithm in greatly reduced time,and in large-scale scenario,it has a convergence good enough to meet the real-time decision requirements of large-scale sensor network.关键词
多传感器协同跟踪/潜博弈/纳什均衡/改进并行最佳响应动态算法Key words
multi-sensor collaborative tracking/potential game/NE/MPBRD algorithm分类
信息技术与安全科学引用本文复制引用
张淯铧,林庆宝,左燕,彭冬亮..基于潜博弈的多传感器协同跟踪分布式优化算法[J].无线电工程,2025,55(3):672-678,7.基金项目
国家自然科学基金(61673146) （61673146）
浙江省自然科学基金重点项目(LZ23F030002)National Natural Science Foundation of China(61673146) （LZ23F030002）
Zhejiang Provincial Natural Science Foundation of China(LZ23F030002) （LZ23F030002）
